diff --git a/modules/model_quant.py b/modules/model_quant.py
index c99ca8945..48bacf0a1 100644
--- a/modules/model_quant.py
+++ b/modules/model_quant.py
@@ -278,16 +278,16 @@ def load_quanto(msg='', silent=False):
 
 
 def upcast_non_layerwise_modules(model, dtype): # pylint: disable=unused-argument
-    from diffusers.hooks.layerwise_casting import SUPPORTED_PYTORCH_LAYERS
+    from diffusers.hooks.layerwise_casting import _GO_LC_SUPPORTED_PYTORCH_LAYERS
     model_children = list(model.children())
     if not model_children:
-        if not isinstance(model, SUPPORTED_PYTORCH_LAYERS):
+        if not isinstance(model, _GO_LC_SUPPORTED_PYTORCH_LAYERS):
             model = model.to(dtype)
         return model
     for module in model_children:
         has_children = list(module.children())
         if not has_children:
-            if not isinstance(module, SUPPORTED_PYTORCH_LAYERS):
+            if not isinstance(module, _GO_LC_SUPPORTED_PYTORCH_LAYERS):
                 module = module.to(dtype)
         else:
             module = upcast_non_layerwise_modules(module, dtype)
diff --git a/modules/processing.py b/modules/processing.py
index bc96fa20a..c574c814e 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -373,8 +373,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     image.info["parameters"] = info
                     output_images.append(image)
 
-            is_grid = len(output_images) == p.batch_size * p.n_iter + 1 and i == 0
-            for j, image in enumerate(output_images):
+            for i, image in enumerate(output_images):
+                is_grid = len(output_images) == p.batch_size * p.n_iter + 1 and i == 0
                 # resize after
                 if p.selected_scale_tab_after == 1:
                     p.width_after, p.height_after = int(image.width * p.scale_by_after), int(image.height * p.scale_by_after)
diff --git a/pipelines/model_wanai.py b/pipelines/model_wanai.py
index 7400bdd10..49503c670 100644
--- a/pipelines/model_wanai.py
+++ b/pipelines/model_wanai.py
@@ -70,7 +70,7 @@ def load_wan(checkpoint_info, diffusers_load_config={}):
             transformer_2 = load_transformer(repo_id, diffusers_load_config, 'transformer_2')
         else:
             shared.log.error(f'Load model: type=WanAI stage="{shared.opts.model_wan_stage}" unsupported')
-            return None 
+            return None
     else:
         transformer = load_transformer(repo_id, diffusers_load_config, 'transformer')
         transformer_2 = None